def sample_iterative(self, stack, result_stack, prev, grammar):
stack.pop()
wrapped_sampler = self._sampler
restartable_sampler = pybo.IterativeSampler(wrapped_sampler,
grammar,
is_restartable=True)
obj = restartable_sampler.sample()
result_stack.append(obj)
def sample_iterative(self, stack, result_stack, prev, grammar):
# We use recursion here for now.
stack.pop()
set_elems_sampler = self._sampler
k = pybo.pois(self._d, self._sampler._precomputed_eval)
sampler = pybo.IterativeSampler(set_elems_sampler, grammar)
set_elems = []
for _ in range(k):
obj = sampler.sample()
set_elems.append(obj)
result_stack.append(self.builder.set(set_elems))
def sample_iterative(self, stack, result_stack, prev, grammar):
if prev is None or self in prev.get_children():
# Sample from lhs with substituted x.
stack.append(self.lhs)
else:
stack.pop()
# Get the object in which the l-atoms have to be replaced from the
# result stack.
core_object = result_stack.pop()
# Replace the atoms and push result.
sampler = pybo.IterativeSampler(self.rhs, grammar)
res = core_object.replace_l_atoms(sampler) # Recursion for now.
result_stack.append(res)
def sample_iterative(self, stack, result_stack, prev, grammar):
if prev is None or self in prev.children:
stack.append(self.lhs)
else:
stack.pop()
# Get the object in which the u-atoms have to be replaced from the
# result stack.
core_object = result_stack.pop()
# Recover the old y from the stack.
# y = result_stack.pop()
# Replace the atoms and push result.
sampler = pybo.IterativeSampler(self.rhs, grammar)
res = core_object.replace_u_atoms(sampler) # Recursion for now.
result_stack.append(res)
def sample_iterative(self, alias):
"""Samples from the rule identified by `alias` in an iterative manner.
Parameters
----------
alias : str
The rule to be sampled from
Traverses the decomposition tree in post-order.
The tree may be arbitrarily large and is expanded on the fly.
"""
try:
sampler = self[alias]
except KeyError:
DecompositionGrammar._missing_rule_error(alias)
return pybo.IterativeSampler(sampler, self).sample()